In statistics, the range is computed as the difference between the minimum and maximum values Range(x) = Max(x) - Min(x) If the operatinal time of KAL CULAS graphics cards are each exponentially distribitued with a mean time of 32 months, compute the expected range of i.i.d. random variables X1, X2, X3, X4; where each random variable represents one graphics card to show your work set up all integrals correctly.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
In statistics, the range is computed as the difference between the minimum and maximum values
Range(x) = Max(x) - Min(x)
If the operatinal time of KAL CULAS graphics cards are each exponentially distribitued with a mean time of 32 months, compute the expected range of i.i.d. random variables X1, X2, X3, X4; where each random variable represents one graphics card to show your work set up all
Step by step
Solved in 2 steps with 13 images
